1. Field of the Invention
The present invention relates to image processing, and more particularly relates to an image enhancement method, an image enhancement device, an object detection method, and an object detection device.
2. Description of the Related Art
When carrying out image processing such as human face detection, moving object tracing, etc., image enhancement is usually involved.
In general, the image enhancement refers to processing of enhancing user-concerned information in an input image so as to let the input image turn clear from unclear or to emphasize some interesting features and limit some non-interesting ones; in this way, the quality of the input image may be improved, the information amount of the input image may be enriched, and the decipherment and recognition effect of the input image may be increased.
The problem of image quality is a big obstacle for detecting specific objects in an input image. In particular, for example, in a video conference system, it may be necessary to detect the position of a human face in a video image. However, when lighting conditions are not good in a conference room, the brightness problem of image quality may cause the performance of a human face detection algorithm to become diminished. At this time, it may be necessary to improve the image quality.
U.S. Pat. No. 7,068,841 discloses a technique of enhancing an input image based on the position of a human face in the input image. This patent determines an image enhancement curve by comprehensively considering image features of a human face area and the whole image so as to carry out enhancement processing with regard to the input image. However, this patent only concerns acquiring an image having good visual effects in whole by enhancing the input image; in the meantime, this kind of enhanced image may reduce the performance of human face detection.
In an application of object detection such as human face detection, if the quality of a video image is not good, an idea of first improving the quality of the video image, and then carrying out object detection is natural. At this time, the following aspects may be considered.
(1) As for object detection, when is an image enhancement algorithm utilized? Sometimes an image has good quality, and does not need to be enhanced, whereas sometimes an image has bad quality, and needs to be enhanced. As a result, as an input of an image enhancement algorithm, it is difficult to determine which images need to be enhanced and which images do not need to be enhanced.
(2) How to choose a parameter of an image enhancement algorithm? As for the same image enhancement algorithm, different parameters may result in totally different enhanced images. As a result, it is difficult to select a proper parameter of an image enhancement algorithm by which an enhanced image best for an object detection algorithm can be generated.
(3) Conventional image enhancement algorithms generally concentrate in generating an image that looks beautiful. However, an image that looks beautiful does not mean that it is always best for the object detection.